Name
Title | ||
|---|---|---|
Unsupervised domain selective graph convolutional network for preoperative prediction of lymph node metastasis in gastric cancer |
Abstract | ||
|---|---|---|
•The proposed MSDA framework can promote LN metastasis prediction in multi-center learning.•A novel 3D IFPN can effectively extract the domain invariant features of small targets (i.e., LNs).•A novel UDS-GCN is designed to achieves the imbalanced knowledge transfer and class-aware feature alignment across domains. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.media.2022.102467 | Medical Image Analysis |
Keywords | DocType | Volume |
Lymph node metastasis,Multi-source domain adaptation,Feature pyramid network,Domain selection,Graph convolutional network | Journal | 79 |
ISSN | Citations | PageRank |
1361-8415 | 1 | 0.35 |
References | Authors | |
0 | 10 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yongtao Zhang | 1 | 5 | 1.08 |
| Ning Yuan | 2 | 1 | 0.35 |
| Zhiguo Zhang | 3 | 102 | 24.92 |
| Jie Du | 4 | 10 | 3.97 |
| Tianfu Wang | 5 | 382 | 55.46 |
| Bing Liu | 6 | 4 | 0.73 |
| Aocai Yang | 7 | 1 | 0.35 |
| Kuan Lv | 8 | 1 | 0.35 |
| Guolin Ma | 9 | 11 | 1.60 |
| Bai Ying Lei | 10 | 119 | 24.99 |